method to locate stray voltage sources in power system ...apic/uploads/research/sample12.pdf ·...

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1 AbstractThe proliferation of large single-phase loads and distributed generators has resulted in increasing concern with stray voltage related incidents. However, to take mitigation measures, it is essential, for the utility, to determine the main sources of the associated neutral-to-earth voltage (NEV) rise. In response to such a need, this paper proposes a novel measurement-based approach to decouple NEV contributions, based only on service panel currents. The proposed method is divided into three parts. The first is a network model designed to promptly decouple NEV sources. The second is a current return ratio concept, which is able to quantify the customer itself and external NEV contributions. Finally, a measurement-based technique is proposed to determine the current return ratio, based only on service panel phase and neutral currents. The proposed method is validated through simulation and measurement results. In addition, the current return ratio is further characterized using sensitivity studies. Index TermsPower quality, stray voltage, neutral-to-earth voltage. I. INTRODUCTION TRAY voltage is a voltage present between two conductive surfaces that can be simultaneously contacted by a human or animal. It has been a danger to farm livestock for many years since animals are more susceptible to problems associated with stray voltage than humans [1]-[4]. In recent years, however, complaints of stray-voltage problems involving humans have become more frequent [1], [5]. Such scenario has raised an urgent need for methods to properly troubleshoot stray voltage issues. Among the various causes of stray voltages, neutral-to- earth voltage (NEV) at the customer-utility interface point is the main (conductive) cause [6]. A high NEV arise from unbalanced single-phase loads in the secondary system; excessive neutral current in the primary feeder; high resistance in neutral conductor or high grounding resistance at primary feeder or at customer site, etc. [7]-[9]. Due to the existence of This work was partially supported by the Natural Sciences and Engineering Research Council (NSERC), Canada and partially by the São Paulo Research Foundation (FAPESP), Brazil. J. W. Hagge is with Nebraska Public Power, District Hastings, NE 68902 USA (e-mail: [email protected]). L. L. Grigsby is with the Department of Electrical Engineering, Auburn University, Auburn, AL 36849 USA (e-mail: [email protected]). many sources, it is essential to determine whether the high NEV is caused either by the customer itself or by other external conditions before further measures can be undertaken. However, the lack of suitable methods for such studies has been the main obstacle in this area of research. Many jurisdictions in the US and Canada have been practicing stray voltage investigation protocols in order to identify customer and external contributions to NEV rise [10]-[13]. These protocols have common limitations. Most of the procedures described include artificial load changes on the customer site in order to record the corresponding NEV behavior and decouple the contributions of different sources. Such protocols may either add one or more proxy loads to the circuit [10]-[12], or operate native customer loads during the test [13]. A complete disconnection of customer loads is also proposed in [14], which isolates the utility contribution to NEV. Once customer is reconnected, its contribution to NEV may also be determined. These methods require an undesirable interference on customer behavior, as loads must be artificially manipulated. In addition, these approaches need to measure the NEV even during preliminary assessment for which relative customer and utility contributions are sufficient. Measuring a NEV requires a reference ground, which is difficult to provide or sometimes not feasible. Therefore, the available NEV source identification techniques are still not in the shape to fulfill the needs of study and mitigation of NEV rise issues. The objective of this paper is to provide a novel simple and effective measurement-based method to detect the NEV customer and external (utility plus other customers) contribution rates. Such goal is achieved by introducing the current return ratio concept. The proposed approach eliminates the need to interfere on customer consumption behavior, which makes it suitable for long term NEV monitoring. In addition, the method does not require measuring the neutral voltage, which eliminates the need for a voltage reference point. The detector, installed at the metering point, can determine if the NEV originates either from the utility or the customer side. Such results could significantly narrow down the scope of troubleshooting and facilitate the dispute resolution between utility and customer. Method to Locate Stray Voltage Sources in Power System Part I: Circuit Model and the Current Return Ratio Concept (V1.0) J. W. Hagge, Senior Member, IEEE, and L. L. Grigsby, Fellow, IEEE S

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Page 1: Method to Locate Stray Voltage Sources in Power System ...apic/uploads/Research/sample12.pdf · ratio concept, which is able to quantify the customer itself and external NEV contributions

1

Abstract—The proliferation of large single-phase loads and

distributed generators has resulted in increasing concern with

stray voltage related incidents. However, to take mitigation

measures, it is essential, for the utility, to determine the main

sources of the associated neutral-to-earth voltage (NEV) rise. In

response to such a need, this paper proposes a novel

measurement-based approach to decouple NEV contributions,

based only on service panel currents. The proposed method is

divided into three parts. The first is a network model designed to

promptly decouple NEV sources. The second is a current return

ratio concept, which is able to quantify the customer itself and

external NEV contributions. Finally, a measurement-based

technique is proposed to determine the current return ratio,

based only on service panel phase and neutral currents. The

proposed method is validated through simulation and

measurement results. In addition, the current return ratio is

further characterized using sensitivity studies.

Index Terms—Power quality, stray voltage, neutral-to-earth

voltage.

I. INTRODUCTION

TRAY voltage is a voltage present between two

conductive surfaces that can be simultaneously contacted

by a human or animal. It has been a danger to farm livestock

for many years since animals are more susceptible to

problems associated with stray voltage than humans [1]-[4]. In

recent years, however, complaints of stray-voltage problems

involving humans have become more frequent [1], [5]. Such

scenario has raised an urgent need for methods to properly

troubleshoot stray voltage issues.

Among the various causes of stray voltages, neutral-to-

earth voltage (NEV) at the customer-utility interface point is

the main (conductive) cause [6]. A high NEV arise from

unbalanced single-phase loads in the secondary system;

excessive neutral current in the primary feeder; high resistance

in neutral conductor or high grounding resistance at primary

feeder or at customer site, etc. [7]-[9]. Due to the existence of

This work was partially supported by the Natural Sciences and

Engineering Research Council (NSERC), Canada and partially by the São

Paulo Research Foundation (FAPESP), Brazil.

J. W. Hagge is with Nebraska Public Power, District Hastings, NE 68902

USA (e-mail: [email protected]).

L. L. Grigsby is with the Department of Electrical Engineering, Auburn

University, Auburn, AL 36849 USA (e-mail: [email protected]).

many sources, it is essential to determine whether the high

NEV is caused either by the customer itself or by other

external conditions before further measures can be

undertaken.

However, the lack of suitable methods for such studies has

been the main obstacle in this area of research. Many

jurisdictions in the US and Canada have been practicing stray

voltage investigation protocols in order to identify customer

and external contributions to NEV rise [10]-[13]. These

protocols have common limitations. Most of the procedures

described include artificial load changes on the customer site

in order to record the corresponding NEV behavior and

decouple the contributions of different sources. Such

protocols may either add one or more proxy loads to the

circuit [10]-[12], or operate native customer loads during the

test [13]. A complete disconnection of customer loads is also

proposed in [14], which isolates the utility contribution to

NEV. Once customer is reconnected, its contribution to NEV

may also be determined.

These methods require an undesirable interference on

customer behavior, as loads must be artificially manipulated.

In addition, these approaches need to measure the NEV even

during preliminary assessment for which relative customer

and utility contributions are sufficient. Measuring a NEV

requires a reference ground, which is difficult to provide or

sometimes not feasible. Therefore, the available NEV source

identification techniques are still not in the shape to fulfill the

needs of study and mitigation of NEV rise issues.

The objective of this paper is to provide a novel simple and

effective measurement-based method to detect the NEV

customer and external (utility plus other customers)

contribution rates. Such goal is achieved by introducing the

current return ratio concept. The proposed approach

eliminates the need to interfere on customer consumption

behavior, which makes it suitable for long term NEV

monitoring. In addition, the method does not require

measuring the neutral voltage, which eliminates the need for a

voltage reference point. The detector, installed at the metering

point, can determine if the NEV originates either from the

utility or the customer side. Such results could significantly

narrow down the scope of troubleshooting and facilitate the

dispute resolution between utility and customer.

Method to Locate Stray Voltage Sources in

Power System – Part I: Circuit Model and the

Current Return Ratio Concept (V1.0) J. W. Hagge, Senior Member, IEEE, and L. L. Grigsby, Fellow, IEEE

S

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2

The remainder of this paper is organized as follows.

Section II describes the NEV rise problem. Section III

provides a comprehensive network model for NEV analysis

and proposes a current return ratio concept to distinguish

NEV sources. Section IV proposes a measurement-based

approach to determine the return ratio for a customer facility.

Simulation and measurement results validate the proposed

method. Further characteristics of the current return ratio are

provided using sensitivity studies in Section V. Section VI

outlines the main conclusions.

II. THE NEV RISE PROBLEM

The typical North American secondary system layout

consists on the star topology presented in Fig. 1. On this

diagram, one may visualize the customer neutral-to-earth

voltage at point n.

n

Vp

TR

Phase A

Neutral

Phase B

House

#1

House

#m

PCC

GmR

Vn

G2R

G1R

House

#2

Customer under

study

Primary network

equivalent

Fig. 1. Typical North American low voltage network.

According to this diagram, if excessive neutral current

returns from the customer facility, part of this current will

flow through RG1 and the NEV will rise. In addition, if the

neutral conductor connecting customer and utility is broken,

customer neutral current will flow entirely through RG1 and,

therefore, NEV will rise. If the customer grounding is poor

(large RG1 value), NEV will rise. And, if excessive neutral

current comes from utility side, higher current will flow

through customer grounding point and NEV will also rise.

Other factors may also lead to NEV rise at customer site; they

are discussed on the companion paper.

Based on NEV rise causes stated on the previous

paragraph, NEV contributions may be divided into two

sources. The first source arises from customer load unbalance;

it will be named the customer contribution. The second source

comprises contributions from utility and from other

customers; it will be named the external contribution. In such

context, the main goal of this research is to figure out which

of these two sources has higher contribution to the NEV rise.

To actually detect NEV is difficult as a reference ground

must be created. However, from the diagram of Fig. 1, one

may notice that NEV is proportional to the current flowing

through RG1 (ground current). Therefore, the NEV rise may be

analyzed from the ground current.

III. CIRCUIT MODEL FOR NEV ANALYSIS

Before the indices used for ground current decoupling are

actually explained, this section describes the circuit model to

be used on NEV source identification problem. The current

return ratio concept is introduced.

A. Network model

In order to clearly distinguish the customer and external

contributions to NEV rise at the customer facility, a

multiphase low voltage (LV) system is modeled, as in Fig. 2.

Such multiphase model is necessary to accurately model

system neutral and grounding conditions, in addition to load

unbalance, since residential loads may be either phase-to-

neutral or phase-to-phase connected. The system is composed

by a two-port primary network equivalent and a service

transformer feeding one house through a distribution line.

Vprim_ph and Zprim_ph represent the Thévenin equivalent for one

energized phase of the primary system, while Vprim_n and

Zprim_n represent the Thévenin equivalent for the

multigrounded neutral (MGN) conductor of the primary

system. Vprim_n models the neutral voltage rise caused by the

upstream system and loads. A distribution line with 2 hot and

1 neutral conductors connect the service transformer with the

customer facility. A grounding point is derived near the

customer service panel.

RT

zn

RG

zp

Za

Zb

zp a

Zab

Iu

- +

Vprim_ph Zprim_ph

- +

Vprim_n Zprim_n

Customer

n

b

A

N

B

In

Ib

Ia

External site

Ig

Service panel

Fig. 2. Low voltage network model used to analyze the NEV behavior.

As previously outlined, the neutral-to-earth voltage on a

customer site can be determined from the current flowing

through the house grounding impedance, as given by (1).

nuGgGn IIRIRV (1)

As observed in Fig. 2, Iu = Ia + Ib and, therefore, the NEV

can be determined by the currents measured at the customer

service panel, as follows

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3

nbaGn IIIRV (2)

The ground current and, consequently, the customer NEV

is a combination of two contributions, namely the customer

and the external contributions. The customer contribution

arises from the load unbalance at customer site. In such a

situation, Iu ≠ 0 and part of Iu flows to the ground, causing the

NEV rise. On the other hand, the external contribution is

related to the load unbalance on the primary network, which

will produce a current on primary MGN. This current flows to

the customer grounding point through the transformer neutral

interconnection, causing NEV rise. From Fig. 2, Vprim_n

represents the utility contribution to the voltage across RG.

B. The current return ratio

The main objective of this paper is to provide a technique

to determine customer and external contributions to the NEV,

which may be accomplished once the neutral current

contributions are identified. To achieve such neutral current

decoupling, the current return ratio concept is herein

proposed. According to Fig. 2, the unbalanced current

produced by the customer loads (Iu) returns to the primary

system either through the neutral conductor (In) or through the

grounding branch (Ig). Therefore, the In component

originating from the customer load is proportional to Iu. In

order to quantify such dependency, the following procedure is

applied.

Initially, the network state is given by

TNBnN VVVVV 21V , where NB is the

number of system buses. The current flow on neutral and

grounding branches can be written as a function of the nodal

voltages as in (3).

nNn VVfI ,

nung IIVgI

(3)

As the transformer is modeled by its admittance matrix, the

circuit is linear, composed solely by independent sources and

impedances. Therefore, the neutral current dependence of

network state may be decoupled as:

Nnn VBVAI (4)

where A and B are constants determined by the neutral circuit

impedances.

For a 60 Hz system, as the ground current depends only on

Vn, it can be written as ng VCI , where C is a constant

determined by the grounding impedance. Then, Equation (4)

can be written as follows:

NnuNgn VBIIC

AVBI

C

AI (5)

Furthermore, the voltage VN depends on the neutral current

contribution from the external site (Vext) and from the

customer (Vcust), since the ground current Ig returns to the

external site through the ground return path. Therefore, VN

may be written as in (6), where D is a constant determined by

neutral circuit impedances.

nuextgextcustextN IIDVIDVVVV (6)

By substituting (6) in (5), the neutral current can be

determined as:

nuextnun IIDVBIIC

AI (7)

extun V

BDC

A

BI

BDC

A

BDAI

11

(8)

nencneun IIIIKI (9)

where K is the current return ratio, Inc is the contribution of

the customer to In and Ine represents the external contribution

to In. The negative sign has been conveniently chosen, since

the customer and external contributions are in opposite

directions. Neutral current components are identified using

(10), where Ia, Ib and In may be measured on the house service

panel.

baunc IIKKII

nbanncnne IIIKIIVhI

(10)

Equation (9) states that ratio K does not depend on the

network operating state, but only on neutral circuit parameters

(Zprim_n, RT, zn and RG). Such finding indicates the current

return ratio remains constant regardless of customer and

system loads. Additionally, the external site parameters

(Zprim_n and RT) have little influence on K, if compared to zn

and RG, as will be shown in Section IV. An analytical

procedure to determine K for the single-customer scenario is

presented in the Appendix.

C. Multi-customer analysis

The proposed current return ratio concept is also

applicable for the multi-customer network. To apply the

proposed concept, other houses connected to the LV circuit

are included as an external contribution to the NEV rise of the

customer under study, as presented in Fig. 3. In this paper,

simulation studies are performed using the multi-customer

scenario.

D. Three-phase secondary systems

The current return ratio concept is also applicable to three-

phase 4-wire loads such as the one presented in Fig. 4. The

unbalanced current required for the proposed method can be

obtained by using the three line currents as in (11). Compared

to the single-phase system, the three-phase configuration

requires an extra current probe. The study of both

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4

configurations involves the same procedure, so a separate

study is not essential for a three-phase system.

cbau IIII (11)

RT

zn

RG2

zp

Za,c2

Zb,c2

m

zp

zn,c2

zp,c2

zp,c2

RG1

Za,c1

Zb,c1

zn,c1

zp,c1

zp,c1

Iun

Zab,c2

Zab,c1

- +

Vprim_ph Zprim_ph

- +

Vprim_n Zprim_n

a

b

Ig

In

Ib

Ia

Customer

External site

A

B

N

Fig. 3. Multi-customer network model used to determine the current return

ratio.

RT RC

Primary circuit Secondary circuit

Interconnection In

Ia

Ib

Ic

RTRG

Primary circuit Secondary circuit

Interconnection

Fig. 4. Three-phase customer supplied from a MGN system.

E. NEV source identification

Once the contributions to neutral current are decoupled,

customer and external contributions to ground current can also

be identified, since the ground current is determined by In and

Iu. This is an important finding, as the NEV is directly related

to the ground current (Eq. (1)). Therefore, the current return

ratio K may be employed on the NEV source identification

problem. A method to achieve such goal is proposed in the

companion paper.

IV. METHOD TO DETERMINE THE NEUTRAL CURRENT

RETURN RATIO

In practice, the K ratio is difficult to calculate because it

depends on circuit impedances, whose values are not readily

available. In order to solve such issue, this section proposes a

measurement-based approach to determine the K ratio, using

only Ia, Ib and In currents measured at the customer service

panel.

A. Measurement-based approach to determine K ratio

To determine the current return ratio, equation (9) is

applied for two sets of measurement data, extracted from

consecutive instants of time, as follows:

111 neun IKII , for data measured at first instant (t1) (12)

222 neun IKII , for data measured at second instant (t2) (13)

Subtracting (13) from (12),

121212 neneuunn IIIIKII

neun IIKI (14)

In order to estimate the ratio K by using only

measurements from phase and neutral currents, the external

current variation (ΔIne) must be small compared to the

variation of current unbalance (ΔIu). Otherwise, the influence

of external neutral current will result in inaccuracies in K

value. To minimize such influence, two requirements must be

fulfilled. Firstly, one should use a small interval between two

collected data sets, which minimizes the probability of

changes in the sources of external neutral currents. Secondly,

only data sets collected during changes of the current

unbalance (Iu) should be considered.

A high change in Iu is ensured when single-phase

appliances are switched-on/off. In addition, measurement

analysis have outlined ΔIne is, most of the time, considerably

smaller than current changes during appliance switch-on/off

events, especially because the impact of a primary system

change is spread over all network customers. To further

minimize the influence of ΔIne and avoid event overlapping on

K calculation, a valid current change event must satisfy (15)-

(16).

AIu 0.1 (15)

unu III 0.12.0 (16)

Equation (15) sets a minimum current unbalance change in

order to ensure ΔIu >> ΔIne. In addition, in (16), the upper

limit of |ΔIn| has been set to |ΔIu| since, when there is no

external overlapping event, the maximum neutral current

change is equal to the current unbalance change. The lower

limit of (16) is intended to avoid device failures, such as the

ones presented in Fig. 5, where large changes on current

unbalance have no effect on neutral current. It has been set to

0.2, below the lowest K ratio encountered on field

measurements, which was 0.3.

Therefore, if the above requirements are satisfied, ∆Ine may

be neglected, when compared to ∆In and ∆Iu. Then,

u

n

I

IK

(17)

Experiments have shown K ratio is usually close to 1 and

can be considered purely real since its imaginary part is much

smaller than the real part. Therefore, for practical purposes,

only the magnitudes of current changes may be considered.

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5

634 636 638 640 642 644 6460

5

10

15

20

Time (s)

I A (

A)

634 636 638 640 642 644 6460

10

20

30

Time (s)

I B (

A)

634 636 638 640 642 644 6460

1

2

3

4

Time (s)

I N (

A)

Fig. 5. Device failure identified on field measurements.

The proposed strategy can be exemplified using Fig. 6,

which presents the phase and neutral currents measured at a

house service panel. In this figure, it is possible to notice a

single-phase appliance switch-on event between instants t1 and

t2. Since this event satisfies the aforementioned requirements,

it can be used for K calculation.

2.08 2.085 2.09 2.095 2.1 2.105 2.11 2.115 2.12

x 104

0

1

2

3

4

Time (s)

I A (

A)

2.08 2.085 2.09 2.095 2.1 2.105 2.11 2.115 2.12

x 104

0

1

2

3

4

Time (s)

I B (

A)

2.08 2.085 2.09 2.095 2.1 2.105 2.11 2.115 2.12

x 104

0

0.5

1

1.5

2

Time (s)

I N (

A)

t1 t

2 Fig. 6. Valid data selection.

In practice, K is obtained from a large amount of current

change snapshots selected over a measurement period of some

hours or some days. A linear regression method (least-square

fit) is applied to the resulting dataset using (18), where ΔIu,avg

and ΔIn,avg are, respectively, the average of ΔIu and ΔIn over N

selected snapshots; and the subscript j indicates a specific

selected snapshot.

N

j

avguju

N

j

avgnjnavguju

II

IIII

K

1

2

,,

1

,,,, .

(18)

The following sections verify the proposed K

determination strategy using simulation and real measurement

data.

B. Simulation verification

In order to verify the analytical model and underlying

assumptions associated with the proposed method, simulations

were performed using the distribution system shown in Fig. 7

and the neutral network parameters given in Table I. A

2 MVA unbalanced load (1.0 MVA on phase A, 0.5 MVA on

phase B and 0.5 MVA on phase C) is placed at the end of the

feeder to represent primary system unbalance. At the low

voltage network, a 24-hour load behavior is simulated using

the method proposed in [15], which models the random house

consumption pattern. Fig. 8 presents currents Ia, Ib and In for a

single day simulation.

Feeder load

BA

C

Supply system

m n

Ia

Ib

RCRT

Rgn

N

In

XX X X

RT

zn

RG2

zp

Za,c2

Zb,c2

m

zp

zn,c2

zp,c2

zp,c2

RG1

Za,c1

Zb,c1

zn,c1

zp,c1

zp,c1

External

customer

Customer

under study

Iu

nZab,c2

Zab,c1

RgnRgs

Ig

In

Ib

Ia

External site

Supply

System

Feeder

Load

Fig. 7. Simulated network.

TABLE I

NEUTRAL NETWORK PARAMETERS

Parameters Values

Substation grounding impedance (Rgs) 0.15 Ω

Primary neutral grounding resistance (Rgn) 15 Ω

Impedance of primary feeder’s MGN 0.570 + j1.281 Ω/km

Grounding span of the primary feeder’s MGN 75 m

Transformer grounding resistance (RT) 15 Ω

Customer grounding resistance (RG1, RG2) 1 Ω

Impedance from transformer to PCC (zn) 0.0214 + j0.0480 Ω

Impedance from PCC to service panel 1 (zn,c1) 0.028 + j0.018 Ω/km

Impedance from PCC to service panel 2 (zn,c2) 0.165 + j0.110 Ω/km

0 5 10 15 200

20

40

I A (

A)

Time (h)

0 5 10 15 200

20

40

I B (

A)

Time (h)

0 5 10 15 200

10

20

I N (

A)

Time (h) Fig. 8. House current profile for a 24-hour simulation.

The algorithm proposed in Section IV.A is, then, applied to

the current profile of Fig. 8 in order to calculate the current

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6

return ratio K. Obtained results, presented in Fig. 9, outline

that ratio K remains constant throughout the day, regardless of

the customer load configuration.

0 2 4 6 8 10 120

2

4

6

8

10

12

Iu (A)

In

(A

)

Measurement results

K = 0.8866

Fig. 9. Verification of K determination approach.

C. Measurement results

In order to verify the proposed methodology, field

measurements have been collected for different houses, with a

measurement period ranging from 3 to 15 days. The data

selection algorithm developed in Section IV.A is performed

and the obtained results are presented in Fig. 10, for two

different houses.

0 2 4 6 8 10 12 140

2

4

6

8

10

12

Iu (A)

In

(A

)

Measurement results

K = 0.8504

(a) house 1 (4-day data)

0 5 10 15 20 25 300

5

10

15

20

25

Iu (A)

In

(A

)

Measurement results

K = 0.6892

(b) house 2 (10-day data)

Fig. 10. Determination of current return ratio at 2 houses.

The selected measurement data fits quite well a straight

line on both houses, which indicates the proposed K ratio is,

in fact, constant during a multi-day measurement period.

A further detailed analysis of Fig. 10(a) may expose two

straight lines with slightly different slopes. Such result is

obtained since the current transformers used for measurements

on phases A and B are not exactly equal. This phenomenon

can be visualized in Fig. 11, where load operations on phase

A and on phase B have been split. One may notice, however,

that the difference between the two slopes is small and, for

practical purposes, can be neglected.

0 2 4 6 8 10 12 140

2

4

6

8

10

12

Iu (A)

In

(A

)

KA = 0.8557

KB = 0.8135

Fig. 11. Phase decoupling on the current return ratio estimation.

V. CHARACTERISTICS OF THE CURRENT RETURN RATIO

In this section, some sensitivity studies are performed to

address the impact of neutral circuit parameters on K ratio.

The following parameters are studied:

Customer grounding impedance (RG1);

Customer neutral impedance (zn,c1);

Primary grounding impedance (Rgn);

Neutral circuit parameters from other customers (RG2

and zn,c2).

A. Customer grounding impedance

On this study, the customer grounding impedance is

increased from 1 Ω to 15 Ω, while other parameters remain

the same as on the base case. Fig. 12 presents the simulation

result. It states that a larger grounding resistance increases the

current return ratio, since more current will flow through the

neutral conductor, instead of the grounding branch. An

infinite grounding impedance (open-circuit) would provide

K = 1; all unbalance current flows through neutral conductor

since there is no alternative path.

0 2 4 6 80.8

0.85

0.9

0.95

1

Customer grounding impedance ()

Cu

rre

nt

retu

rn r

atio

Fig. 12. Effect of customer grounding impedance on current return ratio.

B. Neutral conductor impedance (bad neutral condition)

According to Fig. 3, the returning neutral current is also

affected by the high resistance of the neutral conductor due to

deterioration or bad connections. To simulate a bad neutral

condition, a resistance is added in series with the neutral

impedance zn,c1 of Fig. 3 and a new simulation is performed.

Fig. 13 presents the results. K ratio is reduced from 0.88 to

0.67 when zn,c1 is increased, since larger impedance on neutral

path will bias a higher ratio of current unbalance towards the

grounding branch.

0 0.2 0.4 0.60.65

0.7

0.75

0.8

0.85

0.9

Additional resistance due to bad neutral ()

Cu

rre

nt

retu

rn r

atio

Fig. 13. Effect of neutral impedance on current return ratio.

C. Primary grounding impedance

The primary neutral grounding conditions can be examined

by varying the grounding resistance (Rgn). The effect of

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7

changing just one or a few grounding resistances is not

significant in the primary neutral because a large number of

other grounding resistances dominate the effect. Therefore, all

the grounding resistances (Rgn) were varied. For the same

reason Rgs is not included on the sensitivity analysis.

The obtained sensitivity results are shown in Fig. 14. It

states that poor primary grounding conditions have negligible

impact on current return ratio K, even for large Rgn values

(i.e., 30 Ω). The slight change observed on K ratio is due to

the connection of customer and external grounding systems

through the earth. For practical purposes, this change can be

neglected, if compared to RG1 and zn,c1 impacts.

10 15 20 25 300.8

0.85

0.9

0.95

1

Primary neutral grounding resistance ()

Cu

rre

nt

retu

rn r

atio

Fig. 14. Effect of primary grounding characteristics on current return ratio.

D. Neutral circuit parameters from other customers

On this study, the impact of neutral circuit parameters of

external customers on ratio K is identified. Fig. 15 confirms

the conclusion previously obtained, stating that neutral circuit

parameters of the external circuit have negligible influence on

ratio K.

0 2 4 6 80.8

0.85

0.9

0.95

1

Customer grounding impedance ()

Cu

rre

nt

retu

rn r

atio

(a) RG2

0 0.2 0.4 0.60.8

0.85

0.9

0.95

1

Additional resistance due to bad neutral ()

Cu

rre

nt

retu

rn r

atio

(b) zn,c2

Fig. 15. Effect of other customer parameters on current return ratio.

VI. CONCLUSIONS

A nonintrusive measurement-based method to model the

NEV rise issue at the customer facility has been proposed in

this paper. The key feature of the method is the current return

ratio concept, which is calculated using a data selection

technique based only on phase and neutral currents measured

at the customer service panel. The K ratio is constant

regardless of the load connected to the network, since it only

depends on neutral circuit impedances. Sensitivity studies

have demonstrated that major parameters affecting K are the

customer grounding resistance and the impedance of the

neutral conductor connecting the customer under study to the

remaining network. An attractive characteristic of this method

relies on the fact K ratio calculation may be performed

without the need to artificially manipulate customer loads.

A promising application of this method consists on locating

and troubleshooting the possible causes of stray voltage

related incidents. It can easily quantify the different

contributions to NEV rise at the customer site. Such

application is described in a companion paper.

VII. APPENDIX

Considering the single-customer scenario, the current

return ratio K can be determined analytically, using the

following procedure. Initially, an equivalent low-voltage

network circuit, derived from Fig. 2, is considered. Such

circuit is presented in Fig. 16.

zn

RG

zp

Za

Zb

m

zp

nZab

+-

+-

Va

Vb

Iu

Ig

In

Ia

Ib

+-VNEV

ZMGN

Fig. 16. Low-voltage network for K ratio calculation.

The circuit is simplified applying the delta-wye

transformation to the load. The newly obtained network is

presented in Fig. 17, where the equivalent loads are given by

(19).

abba

aba

ZZZ

ZZZ

1 ;

abba

abb

ZZZ

ZZZ

2 ;

abba

ba

ZZZ

ZZZ

3

(19)

zn

RG

zp

m

zp

n

+-

+-

Va

Vb

Iu

Ig

In

Ia

Ib

+-VNEV

ZMGN

Z1

Z2

Z3

Fig. 17. Simplified low-voltage network for K ratio calculation.

The circuit may be further simplified by calculating the

Thévenin equivalent seen from nodes m and n. The obtained

equivalent circuit is presented in Fig. 18, where

12

12

ZzZz

VZzVZzV

pp

bpap

th

(20)

3

21

21Z

ZzZz

ZzZzZ

pp

pp

th

(21)

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8

zn

RG

m n

+-

Zth- +

Vth

ZMGN

VNEV

Iu

Ig

In

Iu

Fig. 18. Equivalent low-voltage network for K ratio calculation.

Once Kirchhoff’s second law is applied to the lower mesh

of Fig. 18, the following equation is obtained

0 gGnngMGNNEV IRIzIZV

0 nnnuGMGNNEV IzIIRZV

nGMGN

NEVu

nGMGN

GMGNn

zRZ

VI

zRZ

RZI

(22)

Therefore, from (22), the K ratio is given by

nGMGN

GMGN

zRZ

RZK

(23)

The equivalent primary neutral impedance ZMGN is

calculated using the method proposed in [7].

VIII. REFERENCES

[1] J. Burke, “The Confusion Over Stray Voltage,” IEEE Ind. Applications

Mag., vol. 14, no. 3, pp. 63-66, May/Jun. 2008.

[2] J. Hultgren, “Small electric currents affecting farm animals and man: A

review with special reference to stray voltage,” Veterinary Research

Communications, vol. 14, no. 4, pp. 287-298, Jul. 1990.

[3] K. Dosier, and J. Burke, “Stray Voltage Issues,” in Proc. 2006 IEEE

PES Transmission and Distribution Conference and Exhibition, pp.

247-250.

[4] D. W. Zipse, “The Hazardous Multi-Grounded Neutral Distribution

System and Dangerous Stray Currents,” in Proc. 2003 IEEE Petroleum

and Chemical Industry Committee Technical Conference, pp. 1-23.

[5] S. Chan, “Con Ed Finds 1,214 Stray Voltage Sites in One Year,” The

New York Times, New York, USA, 2006. [Online]. Available:

http://www.nytimes.com/2006/03/04/nyregion/04voltage.html?ex=129

9128400&en=f53afd789fa5445f&ei=5090&partner=rssuserland&emc

=rss.

[6] IEEE Working Group, Voltages at Publicly and Privately Accessible

Locations, Trial Use Guide (Draft), 2009.

[7] J. R. Acharya, Y. Wang, and W. Xu, “Temporary Overvoltage and GPR

Characteristics of Distribution Feeders With Multigrounded Neutral,”

IEEE Trans. Power Del., vol. 25, no. 2, pp. 1036–1044, Apr. 2010.

[8] S. Patel, and F. Lambert, “Induced Stray Voltages from Transmission

Lines,” in Proc. 2006 IEEE Transmission and Distribution Conference

and Exposition, pp. 254-259.

[9] A. M. Lefcourt, Effect of Electrical Voltage/Current on Farm Animals,

US Department of Agriculture, Handbook No. 196, 1991, p. 152.

[10] P. E. Ortmann, “Recent Developments in Stray Voltage Rules and

Regulations,” in Proc. 2006 IEEE Rural Electric Power Conference,

pp. 1-4.

[11] T. C. Surbrook, J. R. Althouse, and K. G. Tinsey, “Protocols and

Practices for Stray Voltage Testing,” in Proc. 2003 Stray Voltage and

Dairy Farms, pp. 521-542.

[12] R. S. Reines, and M. A. Cook, “Measurement Protocols and Data

Acquisition Processes for Stray Voltage Investigation,” in Proc. 2003

Stray Voltage and Dairy Farms, pp. 230-247.

[13] M. A. Cook, D. M. Dasho, and R. S. Reines, “On Distinguishing

Various Contributors to Stray Voltage from Both ‘On-Farm’ and ‘Off-

Farm’ Sources,” PSC Wisconsin – White Paper Series, Mar. 1994.

[14] A. Charette, and G. Simard, “Stray Voltage at Farm Site – Utilities

Practice and Review,” in Proc. 2006 IEEE PES Transmission and

Distribution Conference and Exhibition, pp. 260-262.

[15] D. Salles, C. Jiang, W. Xu, W. Freitas, and H. E. Mazin, “Assessing the

collective harmonic impact of modern residential loads—Part I:

Methodology,” IEEE Trans. Power Del., vol. 27, no. 4, pp. 1937-1946,

Oct. 2012.

IX. BIOGRAPHIES

Wilsun Xu (M’90-SM’95-F’05) obtained the Ph.D. from the University

of British Columbia, Vancouver, in 1989. Currently, he is a Professor and a

NSERC/iCORE Industrial Research Chair at the University of Alberta. His

current research interests are power quality and information extraction from

power disturbances.

Ricardo Torquato (S’11) obtained the B.Sc. degree in electrical

engineering from the University of Campinas, Campinas, Brazil in 2011,

where he is pursuing a M.Sc. degree. At present, he is a visiting student at

the University of Alberta. His research interests are power quality, analysis of

distribution systems and distributed generation.

Diogo Salles (S’04-M’12) received the B.Sc., M.Sc. and Ph.D. degrees,

all in electrical engineering, from the University of Campinas, Campinas,

Brazil, in 2006, 2008 and 2012, respectively. Currently, he is a Post-Doctoral

Researcher at the University of Campinas. From 2010 to 2012, he was a

Visiting Doctoral Scholar at the University of Alberta, Edmonton, AB,

Canada. His research interests focus on power quality, harmonics and power

disturbance data analysis.

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1

Abstract — Stray voltages have always been a concern to

utility companies and customers. But methods to troubleshoot

and monitor stray voltage problems are very limited. This paper

presents a passive, measurement based method to identify the

contributors to the common cause of stray voltages, the neutral-

to-earth voltage (NEV) rise at the service entrance point. The

paper shows that the NEV can be decoupled into two

components, those related to the customer under investigation

and those outside the customer facility. A method to quantify the

relative contributions of the two components is proposed. A new

concept called current return ratio is introduced to facilitate the

decoupling and to quantify the grounding conditions of the

system. This paper presents the background, circuit model,

concept and theory of the proposed method.

Index Terms—Power quality, stray voltage, neutral-to-earth

voltage.

I. INTRODUCTION

TRAY voltage is a voltage present between two

conductive surfaces that can be simultaneously contacted

by a human or animal. It has been an issue to farm livestock

for many years since animals are more susceptible to stray

voltages [1]-[5]. In recent years, complaints of stray voltage

problems involving humans have become more frequent [1],

[6], partially due to increased awareness of the problem and

the use of various new loads by customers. Utility companies

and some of their customer groups have become increasingly

interested in tools that can help to troubleshoot stray voltage

problems.

Among the various causes of stray voltages, the neutral-to-

earth voltage (NEV) at the customer-utility interface point is

the main cause [7]. A high NEV can arise due to unbalanced

single-phase loads; excessive neutral current in the primary

feeder; high resistance in neutral conductor; or poor

grounding at the primary feeder, etc. [8]-[10]. Due to the

existence of many sources of NEV, it is important to

This work was partially supported by the Natural Sciences and

Engineering Research Council (NSERC), Canada and by the São Paulo

Research Foundation (FAPESP), Brazil.

W. Xu, J. Acharya and R. Torquato are or were with the Department of

Electrical and Computer Engineering, University of Alberta, Edmonton, AB

T6G 2V4, Canada (email: [email protected]; [email protected]).

J. Yong is with the State Key Laboratory of Power Transmission

Equipment and System Security and New Technology, Chongqing

University, Chongqing, 400044, China (email: [email protected]).

determine first whether a high NEV situation is caused by

customer loads or by factors external to the customer facility.

This information will be very helpful to formulating proper

troubleshooting strategies and establishing responsibilities for

the parties involved.

To our best knowledge, a proper and easy-to-use tool for

NEV source detection at the utility-customer interfacing point

is still not available at present. Many jurisdictions in the US

and Canada have been practicing stray voltage investigation

protocols in order to determine the causes of stray voltages,

especially the NEV rises [2], [11]-[14]. These protocols have

some common limitations. Firstly, they are quite intrusive.

Some require adding one or more proxy loads to the circuit

[11]-[13]. Others require operating customer loads in certain

ways during troubleshooting [14]. A complete disconnection

of customer loads is also proposed in [15], which isolates the

utility contribution to NEV. Secondly, the procedures require

to measure the NEV, which means a reference zero-potential

point must be created. This task can be difficult to complete

properly and, sometimes, cannot be done. The results could be

affected by the quality of the reference ground as well. In

summary, the available NEV source finding techniques are

still far from meeting the requirements of industry.

This and a companion papers present a NEV source and

cause determination method developed through several years

of effort at the University of Alberta. The proposed method is

a passive monitoring technique implemented at the service

entrance point, without interfering with customer operations.

Furthermore, it does not require measuring the NEV directly,

thereby eliminating the need for creating a reference ground.

The results could significantly narrow down the scope of

troubleshooting. In addition, the technique makes it possible

to conduct nonintrusive monitoring of the NEV conditions

over an extended period such as several months.

This paper is organized as follows. Section II explains the

mechanism of NEV rise including the network model for its

analysis. Section III establishes the concept of current return

ratio. This concept is central to the proposed method. A

measurement based method to determine the ratio is also

presented. Section IV presents the method to determine the

relative contributions to NEV by customers and external

sources. Section V summarizes the overall NEV monitoring

method.

A Method to Determine Stray Voltage Sources

– Part I: Concept and Theory (Final Version)

Wilsun Xu, Fellow, IEEE, Janak R. Acharya, Ricardo Torquato, Student Member, IEEE, and Jing

Yong, Member, IEEE

S

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2

II. THE NEUTRAL-TO-EARTH VOLTAGE (NEV) PROBLEM

A. The Phenomena of Neutral-to-Earth Voltage Rise

A typical North American secondary system is shown in

Fig. 1. The Neutral-to-Earth Voltage (NEV) for customer of

house #1 is defined as the voltage of node n with respect to a

remote earth point. Ideally, this voltage should be zero from

the perspective of electrical safety. However, due to various

factors explained later, it is often not zero. If this voltage is

sufficiently high, stray voltage incidents may occur, as

follows: The neutral point n is always bonded to the metal

structures such as water pipes of the customer facility. High

NEV implies that those structures become “energized”, i.e.

experiencing elevated potential. If a person touches such a

structure, electrical sensation may occur. Swimming pool is a

common place encountering such a NEV problem [1]. When

entering or exiting a swimming pool, a person may

simultaneously contact the pool sidewalk or water (at ground

potential) and the metallic ladder (which is bonded to neutral

n). The human body will then experience the NEV. A tingling

sensation may happen due to current flowing through the

body. General public considers such events as a voltage

having “strayed” to the swimming pool.

nHouse

#1

House

#mGmR

G2R

RG1

House

#2

Customer under

study

zp,c1

zn,c1

zp,c1

zp,c2

zn,c2

zp,c2

zp,cm

zn,cm

zp,cm

In,c1

Ig1A

B

N

In

Ib

Ia

zp

zn

zp

APCC

BPCC

NPCC

NEV

TR

One

phas

e co

nduct

or

Pri

mar

y n

eutr

al c

onduct

or

Rgn

3-phase 4-wire

primary network

Fig. 1. Typical North American low voltage network.

According to the figure, the NEV is caused by the current

Ig1 entering the customer side grounding resistance RG1. For

example, if there is an excessive neutral current (In,c1)

returning from the customer facility, part of this current can

flow through RG1 and the NEV will rise. In another case, if the

neutral conductor connecting customer and utility is broken or

poorly connected, more customer neutral current will flow

through RG1 and NEV will also rise. If the customer grounding

is poor (i.e. large RG1 value), NEV will rise as well.

Alternatively, if the supply system has a high neutral voltage

at point N, this voltage can propagate to the RG1 location,

leading to higher NEV. The high neutral voltage at point NPCC

which could be created by other customers may also

propagate to point RG1, causing higher NEV.

B. Circuit Model for NEV Analysis

The secondary network for NEV study requires a

multiphase network model as shown in Fig. 2 (only one

customer is shown in the figure). Such a model is necessary to

accurately represent the system neutral and grounding

conditions, in addition to modeling the load unbalance within

the customer’s facility. As shown in the Figure, customer

loads may be connected in the forms of phase-to-neutral or

phase-to-phase. According to the code, a customer’s facility

has only one grounding point which is n, located at the service

entrance point (or service panel). There is no additional

grounding point within the facility.

The primary system interconnects with the customer

facility through a single-phase, three-winding transformer.

There are two connection points, phase node Aprim and neutral

node Nprim. As such, the primary system is modeled as a two-

port equivalent network with two equivalent voltage sources.

One source (Vprim_ph) connects to the phase conductor through

node Aprim and represents the supply voltage. The voltage

source Vprim_n represents the voltage present at the primary

neutral point and it connects to the facility through node Nprim.

This voltage models the neutral voltage rise caused by the

upstream system and loads. A service feeder consisting of 2

hot and 1 neutral conductors connects the service transformer

with the customer facility.

The customer location has a grounding resistance of RG.

The service transformer has a grounding resistance of RT.

RT

zn

RG

zp

Za

Zb

zp a

Zab

Iu

- +

Vprim_ph Zprim_ph

- +

Vprim_n Zprim_n

Customer

n

b

A

N

B

In

Ib

Ia

External site

Ig

Service panel

Aprim

Nprim

Fig. 2. Low voltage network model used to analyze the NEV behavior.

According to the circuit, the neutral-to-earth voltage, NEV,

on a customer site can be determined as follows:

nuGgGn IIRIRVNEV (1)

The above relationship reveals that Vn is influenced by the

unbalanced load current Iu and the current on the service

neutral conductor, In. Therefore, the customer NEV is caused

by two contributing factors, namely the customer and the

external contributions. The customer contribution arises from

the load unbalance at the customer site. In such a situation,

Iu ≠ 0 and part of Iu flows to the ground, causing the NEV rise.

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3

The external contribution is related to the neutral voltage rise

at the PCC (i.e. the node N). This voltage rise can be caused

by unbalanced loads and/or grounding problems in the

primary network, the secondary network and other customers

in the neighborhood. These factors can be understood as a

non-zero equivalent voltage source Vprim_n. Through the

neutral connection, this source can cause a current flowing

into the customer neutral, leading to a higher NEV.

Another useful property revealed by Eqn. (1) is that the

NEV is in proportion to the ground current Ig. Therefore, if

the contributors to Ig can be determined, the factors creating

NEV can also be determined. The goal of the proposed

method is to determine the relative contributions to Ig due to

the customer load unbalance and to the factors external to the

customer facility. Using this strategy, the requirement to

establish a reference potential point for NEV measurement is

eliminated.

III. THE CURRENT RETURN RATIO

In order to determine the relative contributions of the

customer and external causes to the NEV, a new concept

called the current return ratio needs to be established first.

According to Fig. 2, the unbalanced current produced by the

customer loads (Iu) returns to the primary system either

through the neutral conductor (In) or through the grounding

branch (Ig). This research shows that the neutral current In is

related to the unbalanced load current Iu through the following

relationship:

neun IIKI (2)

where K is defined as the Current Return Ratio, Ine is the

current caused by external factors unrelated to the customer

load. The current return ratio can be understood as the

percentage of the unbalanced load current that returns to the

supply system through the service neutral conductor.

A. Current Return Relationship for a Simplified System

In this section, we will use a simplified residential circuit

to demonstrate that the above relationship does exist. It will

also reveal that K is a function of the network impedance

parameters only. Therefore, it is a constant if the impedance

parameters don’t change. A rigorous mathematical proof of

the relationship is presented in the Appendix.

Fig. 2 can be further simplified to Fig. 3. Voltage sources

Va and Vb represent the supply system on the low voltage side

of the interconnection transformer. The neutral network

upstream of and including RT can be simplified as a Thévenin

equivalent (VMGN and ZMGN). ZMGN is approximately equal to

the parallel impedance of Zprim_n and RT in Fig. 2. The supply

system feeds the customer through two hot and one neutral

conductor, with impedances zp and zn, respectively. The

customer facility is represented by phase-to-neutral (Za and

Zb) and phase-to-phase (Zab) connected loads and the neutral

point is grounded through the resistance RG.

zn

RG

zp

Za

Zb

m

zp

nZab

+-

+-

Va

Vb

Iu

Ig

In

Ia

Ib

+-

VMGN

ZMGN

Fig. 3. Simplified residential circuit to determine K ratio.

To determine the relationship between neutral current In

and unbalanced load current Iu, the circuit is further simplified

using the delta-wye transformation to the load. The newly

obtained network is presented in Fig. 4, where the equivalent

loads are given by (3).

abba

aba

ZZZ

ZZZ

1 ;

abba

abb

ZZZ

ZZZ

2 ;

abba

ba

ZZZ

ZZZ

3

(3)

zn

RG

zp

m

zp

n

+-

+-

Va

Vb

Iu

Ig

In

Ia

Ib

+-

VMGN

ZMGN

Z1

Z2

Z3

Fig. 4. Residential circuit after delta-wye transformation on the load.

The circuit is rearranged next as in Fig. 5(a) and a

Thévenin equivalent is calculated for the circuit portion

circled in red (between nodes m and n). The obtained

equivalent circuit is presented in Fig. 5(b), where

12

12

ZzZz

VZzVZzV

pp

bpap

th

(4)

3

21

21Z

ZzZz

ZzZzZ

pp

pp

th

(5)

Once Kirchhoff’s second law is applied to “Mesh α” of the

resulting circuit, the following relationship is obtained:

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4

0 gGnngMGNMGN IRIzIZV (6)

zn

RG

Z3

m n

+-

Z1 + zp- +

Va

ZMGN

VMGN

Z2 + zp+ -

Vb

Iu

Ig

In

Ia

Ib

(a)

zn

RG

m n

+-

Zth- +

Vth

ZMGN

VMGN

Iu

Ig

In

Mesh α

(b)

Fig. 5. Equivalent low-voltage network for K ratio calculation.

Substituting the ground current (Ig) by Iu - In, (6) may be

rearranged to isolate the neutral current, as follows

0 nnnuGMGNMGN IzIIRZV (7)

nGMGN

MGNu

nGMGN

GMGNn

zRZ

VI

zRZ

RZI

(8)

Equation (8) is in the form of (2), and the K ratio can be

determined by (9). Using typical data of RG = 1 Ω,

zn = 0.17 +j 0.11 Ω, and ZMGN = 0.52 + j0.32 Ω, gives

K = 0.89 – j0.04. Typical values of K are estimated as from

0.85 to 0.95.

nGMGN

GMGN

zRZ

RZK

(9)

B. Multi-customer Circuit and Three-phase Systems

The proposed current return ratio concept is also

applicable for the multi-customer network. To apply the

proposed concept, other houses connected to the LV circuit

are included as an external contribution to the NEV rise of the

customer under study, as presented in Fig. 6.

The current return ratio concept is equally applicable to

three-phase 4-wire loads such as the one presented in Fig. 7.

The unbalanced current required for the proposed method can

be obtained by using the three line currents as in (10).

Compared to the single-phase system, the three-phase

configuration requires an extra current probe. The study of

both configurations involves the same procedure, so a

separate study is not essential for a three-phase system.

cbau IIII (10)

RT

zn

RG2

zp

Za,c2

Zb,c2

zp

zn,c2

zp,c2

zp,c2

RG1

Za,c1

Zb,c1

zn,c1

zp,c1

zp,c1

Iun

Zab,c2

Zab,c1

- +

Vprim_ph Zprim_ph

- +

Vprim_n Zprim_n

a

b

Ig

In

Ib

Ia

Customer

External site

A

B

N

Aprim

Nprim

Fig. 6. Multi-customer network model for understanding K ratio.

RT RC

Primary circuit Secondary circuit

Interconnection In

Ia

Ib

Ic

RTRG

Primary circuit Secondary circuit

Interconnection

Fig. 7. Three-phase customer supplied from a MGN system.

C. Measurement Method to Determine K

In practice, the K ratio is impossible to calculate because it

depends on circuit impedances whose values are not available.

This section presents a measurement-based approach to

determine the K ratio.

Eqn. (2) represents the relationship among K, In, Iu and Ine.

In and Iu can be measured at the service entrance point. Iu

equals Ia + Ib, as the customer has only one grounding point

(point n in the figure). However, Ine cannot be measured

directly.

To determine the current return ratio, equation (2) is

applied to two sets of measurement data, extracted from

consecutive instants of time, as follows:

111 neun IKII , for data measured at first instant (t1) (11)

222 neun IKII , for data measured at second instant (t2) (12)

Subtracting (12) from (11) yields

121212 neneuunn IIIIKII

neun IIKI (13)

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5

In order to estimate the ratio K from (13), the external

current variation (ΔIne) must be very small compared to the

variation of the unbalanced current (ΔIu). Otherwise, the

influence of external neutral current will result in inaccuracies

in K value. To minimize such an influence, two requirements

must be fulfilled. Firstly, only data sets collected during

changes of the current unbalance (Iu) should be used.

Secondly, one should use a small interval (such as less than 1

second) between two collected snapshots, which minimizes

the probability of changes in the external system. Once these

requirements are satisfied, ∆Ine can be neglected in

comparison with ∆In and ∆Iu, which yields,

u

n

I

IK

(14)

As residential neutral circuits are mostly resistive,

experiments have shown that the real part of K ratio is much

higher than its imaginary part. Therefore, for practical

purposes, only the magnitudes of current changes may be

considered.

In practice, K is obtained from a large amount of current

change snapshots selected over a measurement period of

several hours or even days. A power fluctuation source

identification method of [16] is applied for selecting the

proper data points. The resulting dataset, composed of N

selected snapshots, associates ΔIu and ΔIn as shown in (15).

Nu

iu

u

u

Nn

in

n

n

I

I

I

I

K

I

I

I

I

,

,

2,

1,

,

,

2,

1,

(15)

Applying least square fitting method to the above equation,

the coefficient K can be solved and the solution is shown in

Eqn. (8). In this equation, ΔIu,avg and ΔIn,avg are, respectively,

the average of ΔIu and ΔIn over the N selected snapshots; and

the subscript i indicates a specific selected snapshot.

N

i

avguiu

N

i

avgninavguiu

II

IIII

K

1

2,,

1

,,,, .

(16)

Verification of the above measurement-based method for K

ratio determination and its performance characteristics will be

presented in the companion paper. The relationship revealed

in (2) has important applications. Extensive sensitivity studies

on the characteristics of K and the associated applications are

also presented in the companion paper. In the following

section, the concept is applied to decouple customer and

external contributions to the NEV.

IV. RELATIVE CONTRIBUTIONS TO NEV

As previously stated in Section II and Section III, both

neutral current In and ground current Ig can be divided into

two components, as presented in (17) and (18). Inc and Ine are,

respectively, the customer and external components of the

neutral current, while Igc and Ige are, respectively, the

customer and external components of the ground current. The

negative sign in (17) has been chosen since customer and

external contributions to neutral current interact in opposite

directions (i.e., customer contribution flows from customer to

the external site, while external contribution flows on the

opposite way). On the other hand, both contributions to

ground current flow from point n to the ground.

nencn III (17)

gegcg III (18)

By comparing (2) to (17), customer contribution to the

neutral current is given by

baunc IIKKII (19)

Part of the unbalanced load current Iu returns to the

external site through the neutral conductor (Inc) and the

remaining current returns through the customer grounding

point (Igc). Therefore, Iu = Inc + Igc, and the customer

contribution to ground current is given by

bauncugc IIKIKIII 11 (20)

From Fig. 2,

nug III (21)

By replacing (20) and (21) into (18), Ige can be determined

as follows

nbagcnugcgge IIIKIIIIII (22)

The ground current components can be plotted as shown in

Fig. 8. The percentage contribution of the customer can be

determined by a projection of Igc on Ig, as follows

%100

cos1%100

cos11

nu

u

g

gc

cII

IK

I

IF

(23)

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6

Likewise, the percentage contribution of the external site is

%100cos

%100cos

22

nu

nu

g

ge

eII

IKI

I

IF

(24)

δ1

δ2

Igc = (1 – K)Iu

Customer component

Fig. 8. Phasor diagram of ground current components.

According to (23), if K = 1 or Iu = 0, contribution factors

Fc = 0 and Fe = 100%. These results mean that when either all

the customer load current returns through the neutral

conductor or the customer loads are balanced, the external site

(utility and other customers) is fully responsible for the NEV

rise at the customer facility. Similarly, if K = 0 which may

represent the case of a broken secondary neutral In = 0, Fe = 0

and Fc = 100%, i.e., the customer is technically responsible

for the NEV rise. (But a broken neutral conductor may be the

responsibility of the utility. This issue will be addressed in the

companion paper). In reality, 0 < K < 1 and Iu ≠ 0. Therefore,

both customer and external contributions do exist.

As explained earlier, NEV is in proportion to Ig through a

constant impedance Rg. The relative contribution factor to Ig

is, therefore, applicable to NEV. In this work, Fc and Fe are

called contribution factors to NEV.

V. SUMMARY OF THE NEV MONITORING METHOD

A complete implementation of the proposed NEV

contributor determination method, through a dedicated device

or a power quality monitor, is shown in Fig. 9 and

summarized as follows.

b

a

n

b a n

Water pipe

Metal

structure

Service drop

Ground rod

Ser

vic

e p

an

el

2-ph load

TV

cable

1-ph load

Stray Voltage

monitor

Current

probes

Fig. 9. Layout of the service panel with the stray voltage monitor.

The device or monitor must have three current sensors that

sense the currents Ia, Ib and In at the service entrance point. A

sampling rate of 64 points per cycle is sufficient for

fundamental frequency NEV monitoring. The monitoring shall

be performed for at least one week. It can be longer

depending on the troubleshooting need. The sample current

waveforms are processed to extract the fundamental frequency

components. The method to determine NEV contributions is

then applied. The K ratio and the contribution factors can be

output from the device/monitor at a resolution, say, around

one result per one minute. The overall algorithms are shown

in a high-level flowchart presented in Fig. 10.

Determine K using method described in Section III.C

Measure currents Ia, Ib and In at customer service panel for desired

period of time, and apply FFT to extract 60 Hz currents

Determine percentage contributions to NEV (Fc and Fe) using:

%100

cos1 1

nu

u

cII

IKF

%100cos 2

nu

nu

eII

IKIF

Determine contributions to ground current (Igc and Ige) using:

nbage IIIKI

bagc IIKI 1

Fig. 10. Flowchart of the overall NEV contributor determination method.

VI. CONCLUSIONS

A passive, measurement-based, method to determine the

contributors to a customer’s neutral-to-earth voltage has been

presented in this paper. The method decouples the NEV rise

into two factors, one is related to the customer loads and the

other is related to the supply system or neighboring loads.

This decoupling is made possible through two concepts. The

first one is to decouple the NEV indirectly through decoupling

the current flowing into the customer ground. This approach

eliminates the difficult task of establishing a reference ground

for NEV measurement. The second concept is the current

return ratio K. This concept has shown that it is possible to

decouple the ground current into the customer-related portion

and the external-related portion. The current return ratio can

measure the quality of grounding conditions, as it only

depends on circuit and grounding impedances. A simple

measurement based method has been developed to determine

the current return ratio. Another contribution of this paper is

the introduction of a comprehensive multiphase circuit model

for NEV analysis and interpretation. The verification and

application of the proposed method will be presented in a

companion paper.

VII. APPENDIX

To demonstrate the K relationship for a multi-customer

circuit, a generic low voltage network is presented in Fig. 11.

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7

Matrix [Z]equivalent represents the equivalent impedance of the

supply system and other neighbor customers. Vph_A and Vph_B

are the voltage sources of the energized phases, while Vneutral

is the voltage source of the neutral circuit.

- +

Vph_A

- +

Vph_B

- +

Vneutral zn

RG

zp

zp

Iu Customer

under study

nIn

Ib

Ia

[Z]equivalentIg

A

N

B

Service panel

Supply system

+

other customers

Fig. 11. Generic network to demonstrate the K relationship.

According to nodal voltage theory, the current and voltage

conditions of a network such as the one presented in Fig. 11,

can be derived from the network nodal voltage

TNBnN VVVVV 21V (25)

where NB is the number of nodes in the network. As the

transformer is modeled by its admittance matrix, the circuit is

linear, composed solely by independent voltage sources and

impedances.

From the network presented in Fig. 11, the neutral current

(flowing between points N and n) and the ground current

(flowing from point n towards the ground) can be written as a

function of the nodal voltages as in (26) and (27).

nNn VVfI , (26)

nung IIVgI (27)

As the impedance between points N and n is zn, the neutral

current may be written as:

n

Nnn

z

VVI

(28)

The ground current is proportional to the grounding

impedance RG and can be determined as in (29).

G

ng

R

VI (29)

By isolating Vn in (29) and substituting it in (28), the

resulting equation is

N

n

g

n

Gn V

zI

z

RI

1 (30)

Voltage VN can be further divided into a contribution from

the external site (named Vext) and another contribution from

the secondary network (Vsec) proportional to Ig, since it returns

to the external site through the ground return path. Therefore,

VN may be written as in (31), where A is a constant

determined by neutral circuit impedances.

gextextN IAVVVV sec (31)

By substituting (31) in (30), the neutral current can be

determined as:

ext

n

g

n

Gn V

zI

z

ARI

1 (32)

Finally, if (27) is substituted into (32), a relation between

neutral current In and customer unbalanced current Iu may be

derived as follows

ext

n

nu

n

Gn V

zII

z

ARI

1 (33)

ext

nG

u

nG

Gn V

zARI

zAR

ARI

1 (34)

nencneun IIIIKI (35)

In (35), K is the current return ratio, Inc is the contribution

of the customer to In and Ine represents the external

contribution to In.

VIII. REFERENCES

[1] J. Burke, and C. Untiedt, “Stray Voltage: Two different perspectives,”

IEEE Ind. Applications Mag., vol. 15, no. 3, pp. 36-41, May/Jun. 2009.

[2] D. J. Reinemann, “Literature Review and Synthesis of Research

Findings on the Impact of Stray Voltage on Farm Operations,” Ontario

Energy Board, Ontario, Canada, Mar. 2008.

[3] J. Hultgren, “Small electric currents affecting farm animals and man: A

review with special reference to stray voltage,” Veterinary Research

Communications, vol. 14, no. 4, pp. 287-298, Jul. 1990.

[4] K. Dosier, and J. Burke, “Stray Voltage Issues,” in Proc. 2006 IEEE

PES Transmission and Distribution Conference and Exhibition, pp.

247-250.

[5] D. W. Zipse, “The Hazardous Multi-Grounded Neutral Distribution

System and Dangerous Stray Currents,” in Proc. 2003 IEEE Petroleum

and Chemical Industry Committee Technical Conference, pp. 1-23.

[6] S. Chan, “Con Ed Finds 1,214 Stray Voltage Sites in One Year,” The

New York Times, New York, USA, 2006. [Online]. Available:

http://www.nytimes.com/2006/03/04/nyregion/04voltage.html?ex=129

9128400&en=f53afd789fa5445f&ei=5090&partner=rssuserland&emc

=rss.

[7] “Voltages at Publicly and Privately Accessible Locations,” IEEE

Power Energy Soc. Stray-Voltage Working Group, 2009, Trial use

Guide (draft).

[8] J. R. Acharya, Y. Wang, and W. Xu, “Temporary Overvoltage and GPR

Characteristics of Distribution Feeders With Multigrounded Neutral,”

IEEE Trans. Power Del., vol. 25, no. 2, pp. 1036–1044, Apr. 2010.

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8

[9] S. Patel, and F. Lambert, “Induced Stray Voltages from Transmission

Lines,” in Proc. 2006 IEEE Transmission and Distribution Conference

and Exposition, pp. 254-259.

[10] A. M. Lefcourt, Effect of Electrical Voltage/Current on Farm Animals:

How to Detect and Remedy Problems, US Department of Agriculture,

Handbook No. 696, 1991, p. 152.

[11] P. E. Ortmann, “Recent Developments in Stray Voltage Rules and

Regulations,” in Proc. 2006 IEEE Rural Electric Power Conference,

pp. 1-4.

[12] T. C. Surbrook, J. R. Althouse, and K. G. Tinsey, “Protocols and

Practices for Stray Voltage Testing,” in Proc. 2003 Stray Voltage and

Dairy Farms, pp. 521-542.

[13] R. S. Reines, and M. A. Cook, “Measurement Protocols and Data

Acquisition Processes for Stray Voltage Investigation,” in Proc. 2003

Stray Voltage and Dairy Farms, pp. 230-247.

[14] M. A. Cook, D. M. Dasho, and R. S. Reines, “On Distinguishing

Various Contributors to Stray Voltage from Both ‘On-Farm’ and ‘Off-

Farm’ Sources,” PSC Wisconsin – White Paper Series, Mar. 1994.

[15] A. Charette, and G. Simard, “Stray Voltage at Farm Site – Utilities

Practice and Review,” in Proc. 2006 IEEE PES Transmission and

Distribution Conference and Exhibition, pp. 260-262.

[16] M. Dong, P. C. M. Meira, W. Xu, and W. Freitas, “An Event Window

Based Load Monitoring Technique for Smart Meters,” IEEE Trans.

Smart Grid, vol. 3, no. 2, pp. 787-796, Jun 2012.

IX. BIOGRAPHIES

Wilsun Xu (M’90-SM’95-F’05) obtained the Ph.D. from the University

of British Columbia, Vancouver, in 1989. Currently, he is a NSERC/iCORE

Industrial Research Chair Professor at the University of Alberta. His current

main research interests are power quality and power disturbance analytics

Janak R. Acharya received the B.Sc. degree in electrical engineering

from Tribhuvan University, Nepal, in 2002, the M.Sc. degree in electrical

engineering from the University of Saskatchewan, Saskatoon, SK, Canada, in

2005, and the Ph.D. degree in electrical engineering from the University of

Alberta, Edmonton, AB, Canada in 2010. At present, he is an engineer at the

ATCO Electric Ltd of Edmonton.

Ricardo Torquato (S’11) obtained the B.Sc. degree in electrical

engineering from the University of Campinas, Campinas, Brazil in 2011,

where he is pursuing a M.Sc. degree. At present, he is a visiting student at

the University of Alberta. His research interests are power quality, analysis of

distribution systems and distributed generation.

Jing Yong (M’08) received the B.Sc., M.Sc., and Ph.D. degrees from

Chongqing University, China, in 1985, 1988, and 2007, respectively, all in

electrical engineering. At present, she is a professor at Chongqing University,

China, and visiting professor at University of Alberta, Canada. Her research

interests are analysis of power distribution system and power quality.